Data Scientist (Machine Learning) at Flintex Consulting Pte Ltd | SGP | Rezi

Data Scientist (Machine Learning) at Flintex Consulting Pte Ltd

Data Scientist (Machine Learning)

Flintex Consulting Pte Ltd · SGP

3 weeks ago

Data Scientist (Machine Learning)

Flintex Consulting Pte Ltd · SGP

a month ago
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About the Role

We are seeking a Data Scientist (Machine Learning) to develop and deploy advanced analytics and machine learning solutions that support business operations and digital transformation initiatives. The successful candidate will work closely with cross-functional teams to analyze large datasets, build predictive models, and deliver actionable insights to improve operational efficiency and business performance.

Responsibilities

  • Develop, train, validate, and deploy machine learning models for predictive analytics and optimization.
  • Analyze structured and unstructured datasets to identify trends, patterns, and business opportunities.
  • Design and implement data pipelines for data collection, cleansing, feature engineering, and model training.
  • Build forecasting, classification, regression, clustering, and anomaly detection models.
  • Collaborate with business stakeholders to understand requirements and translate them into data-driven solutions.
  • Evaluate model performance and continuously improve model accuracy and reliability.
  • Develop dashboards and reports to communicate insights and recommendations.
  • Work with data engineers to integrate machine learning models into production systems.
  • Ensure data quality, governance, and compliance with organizational standards.
  • Research and evaluate new machine learning algorithms and emerging technologies.

Requirements

  • Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related discipline.
  • 3–8 years of experience in Data Science, Machine Learning, or Advanced Analytics.
  • Strong programming skills in Python (Pandas, NumPy, Scikit-learn).
  • Experience with machine learning frameworks such as TensorFlow, PyTorch, or XGBoost.
  • Strong knowledge of supervised and unsupervised learning techniques.
  • Experience with SQL and relational databases.
  • Familiarity with cloud platforms such as AWS, Azure, or GCP.
  • Experience with data visualization tools such as Power BI or Tableau.
  • Knowledge of Git, Docker, and MLOps concepts is an advantage.
  • Strong analytical, problem-solving, and communication skills.

Skills

  • Time-series forecasting
  • Predictive maintenance
  • Optimization techniques
  • Operations research
  • Big data technologies (Spark, Hadoop)
  • Generative AI
  • Large Language Models (LLMs)
  • Utilities sector experience
  • Energy sector experience
  • Manufacturing sector experience
  • Industrial sectors experience

Experience Level

  • 3-8 years

Education Level

  • Bachelor's degree
  • Master's degree